{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 2"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn import svm\n",
    "\n",
    "####Problem 2\n",
    "\n",
    "#原始图\n",
    "x = np.array([[1, 0], [0, 1], [0, -1], [-1, 0], [0, 2], [0, -2], [-2, 0]])\n",
    "z = np.array([-1, -1, -1, +1, +1, +1, +1])\n",
    "\n",
    "x1 = x[z>0][:, 0]\n",
    "y1 = x[z>0][:, 1]\n",
    "x2 = x[z<0][:, 0]\n",
    "y2 = x[z<0][:, 1]\n",
    "\n",
    "plt.scatter(x1, y1)\n",
    "plt.scatter(x2, y2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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8DXhPVZ0N/B/w5vGW1M1wOelC4G+XchyDfUyG69EfAa6vqhvHXU8fhr8m/zPwojGXMopnAxcO16Y/BDw/yQfHW9Loqure4fN9wEeBc8Zb0Uj2A/uP+Q3ww8wG/SR7MfC5qvrGUg5isI/B8APH9wF3VdWfjLueLpKsTbJ6+PMqhpubj7eqxauqK6tqXVVtZPZX5X+sqsvGXNZIkpw8/FCe4dLFC4GJu5Osqr4O3JPk6K7P5wITd4PBQ1zKMuwR3cdm1ssmyQ3ALwBrkuwHfr+q3jfeqkbybOAVwJ7h2jTAW6rqk2OsaVSnAe8fftL/KGB7VU30rYIN+Cngo7PXD5wE/HVV/cN4SxrZ64Hrh0sYXwZeNeZ6RpbkMcALgFcv+ViTdLujJGlhLsVIUmMMdklqjMEuSY0x2CWpMQa7JDXGYJekxhjsktQYg12SGvP/Oh75Kso3XtcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#特征转换之后的图\n",
    "def phi_1(x):\n",
    "    return x[1] ** 2 - 2 * x[0] + 3\n",
    "\n",
    "def phi_2(x):\n",
    "    return x[0] ** 2 - 2 * x[1] - 3\n",
    "\n",
    "X = []\n",
    "for i in x:\n",
    "    X.append([phi_1(i), phi_2(i)])\n",
    "X = np.array(X)\n",
    "    \n",
    "X1 = X[z>0][:, 0]\n",
    "Y1 = X[z>0][:, 1]\n",
    "X2 = X[z<0][:, 0]\n",
    "Y2 = X[z<0][:, 1]\n",
    "\n",
    "plt.scatter(X1,Y1)\n",
    "plt.scatter(X2,Y2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#曲线图\n",
    "y3 = np.arange(-2, 2, 0.01)\n",
    "x3 = np.array([(i * i - 1.5) / 2 for i in y3])\n",
    "\n",
    "plt.scatter(x1, y1)\n",
    "plt.scatter(x2, y2)\n",
    "plt.scatter(x3, y3, s=1)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "SVC(C=10000000000.0, cache_size=200, class_weight=None, coef0=1,\n",
       "  decision_function_shape='ovr', degree=2, gamma=1, kernel='poly',\n",
       "  max_iter=-1, probability=False, random_state=None, shrinking=False,\n",
       "  tol=0.001, verbose=False)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf = svm.SVC(kernel='poly', degree=2, coef0=1, gamma=1, C=1e10, shrinking=False)\n",
    "clf.fit(x, z)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1, 2, 3, 4, 5])"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.support_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[-0.64491963, -0.76220325,  0.88870349,  0.22988879,  0.2885306 ]])"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.dual_coef_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([0.64491963, 0.76220325, 0.88870349, 0.22988879, 0.2885306 ])"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "z[clf.support_] * clf.dual_coef_[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 4"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "-1.6663314053609206"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "b = clf.intercept_[0]\n",
    "b"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[ 0,  1],\n",
       "       [ 0, -1],\n",
       "       [-1,  0],\n",
       "       [ 0,  2],\n",
       "       [ 0, -2]])"
      ]
     },
     "execution_count": 65,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x[clf.support_]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 66,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([-0.64491963, -0.76220325,  0.88870349,  0.22988879,  0.2885306 ])"
      ]
     },
     "execution_count": 66,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "clf.dual_coef_[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 67,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#点的数量\n",
    "n = 1000\n",
    "r = 3\n",
    "\n",
    "#作点\n",
    "a = np.linspace(-r, r, n)\n",
    "b = np.linspace(-r, r, n)\n",
    "\n",
    "#构造网格\n",
    "A, B = np.meshgrid(a, b)\n",
    "X = np.c_[A.reshape(-1, 1), B.reshape(-1, 1)]\n",
    "label = np.reshape(clf.predict(X), A.shape)\n",
    "\n",
    "#绘制等高线\n",
    "plt.contour(A, B, label, 0)\n",
    "\n",
    "plt.scatter(x1, y1)\n",
    "plt.scatter(x2, y2)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 15"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "####Problem 15\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "from sklearn import svm\n",
    "\n",
    "def transformdata(file):\n",
    "    data = np.genfromtxt(file)\n",
    "    y, X = data[:, 0], data[:, 1:]\n",
    "    return X, y\n",
    "\n",
    "train = \"featurestrain.txt\"\n",
    "X_train, y_train = transformdata(train)\n",
    "test = \"featurestest.txt\"\n",
    "X_test,y_test = transformdata(test)\n",
    "\n",
    "#作图\n",
    "plt.scatter(X_train[y_train == 0][:, 0], X_train[y_train == 0][:, 1], s=1, label='0')\n",
    "plt.scatter(X_train[y_train != 0][:, 0], X_train[y_train != 0][:, 1], s=1, label='not 0')\n",
    "plt.title('0 VS not 0')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#训练模型并作图\n",
    "y_train_1 = (y_train==0).astype(\"int\")\n",
    "C = [-6, -4, -2, 0, 2]\n",
    "W = []\n",
    "\n",
    "for i in C:\n",
    "    c = 10 ** i\n",
    "    clf = svm.SVC(kernel=\"linear\", C=c)\n",
    "    clf.fit(X_train, y_train_1)\n",
    "    w = clf.coef_\n",
    "    W.append(np.linalg.norm(w))\n",
    "\n",
    "plt.plot(C, W)\n",
    "plt.title(\"$||w||$ vs $log_{10}C$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 16"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "####Problem 16\n",
    "plt.scatter(X_train[y_train == 8][:, 0], X_train[y_train == 8][:, 1], s=1, label='8')\n",
    "plt.scatter(X_train[y_train != 8][:, 0], X_train[y_train != 8][:, 1], s=1, label='not 8')\n",
    "plt.title('8 VS not 8')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#训练\n",
    "y_train_8 = 2 * (y_train==8).astype(\"int\") - 1\n",
    "C = [-6, -4, -2, 0, 2]\n",
    "Ein = []\n",
    "alpha = []\n",
    "for i in C:\n",
    "    c = 10 ** i\n",
    "    clf = svm.SVC(kernel='poly', degree=2, coef0=1, gamma=1, C=c)\n",
    "    clf.fit(X_train, y_train_8)\n",
    "    e = np.mean(clf.predict(X_train) != y_train_8)\n",
    "    #支持向量的索引\n",
    "    support = clf.support_\n",
    "    #计算系数\n",
    "    coef = np.sum(clf.dual_coef_[0] * y_train_8[support])\n",
    "    alpha.append(coef)\n",
    "    Ein.append(e)\n",
    "\n",
    "#作图\n",
    "plt.plot(C, Ein)\n",
    "plt.title(\"$\\log_{10}C$ VS $E_{in}$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 17"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "####Problem 17\n",
    "plt.plot(C, alpha)\n",
    "plt.title(\"$\\log_{10}C$ VS sum_alpha\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 18"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "####Problem 18\n",
    "C = [-3, -2, -1, 0, 1]\n",
    "Distance = []\n",
    "#将标签修改为-1, 1\n",
    "y = 2 * y_train_1 - 1\n",
    "\n",
    "for i in C:\n",
    "    c = 10**i\n",
    "    clf = svm.SVC(kernel='rbf', gamma=1, C=c)\n",
    "    clf.fit(X_train, y)\n",
    "    X = X_train[clf.support_]\n",
    "    #距离矩阵\n",
    "    d1 = np.sum(X ** 2, axis=1).reshape(-1, 1)\n",
    "    d2 = np.sum(X ** 2, axis=1).reshape(1, -1)\n",
    "    dist = d1 + d2 - 2 * X.dot(X.T)\n",
    "    #Kernel矩阵\n",
    "    K = np.exp(- c * dist)\n",
    "    #计算anyn\n",
    "    y1 = clf.dual_coef_[0] * y[clf.support_]\n",
    "    w2 = y1.dot(K).dot(y1.T)\n",
    "    #计算距离\n",
    "    distance = 1 / np.sqrt(w2)\n",
    "    Distance.append(distance)\n",
    "    \n",
    "plt.plot(C, Distance)\n",
    "plt.title(\"$\\log_{10}C$ VS distance\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 19"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "####Problem 19\n",
    "y_test_1 = (y_test == 0)\n",
    "\n",
    "Gamma = range(5)\n",
    "Eout = []\n",
    "\n",
    "for i in Gamma:\n",
    "    gamma = 10**i\n",
    "    clf = svm.SVC(kernel='rbf', gamma=gamma, C=0.1)\n",
    "    clf.fit(X_train, y_train_1)\n",
    "    e = np.mean(clf.predict(X_test) != y_test_1)\n",
    "    Eout.append(e)\n",
    "    \n",
    "plt.plot(Gamma, Eout)\n",
    "plt.title(\"$\\log_{10}\\gamma$ VS $E_{out}$\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Problem 20"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "####Problem 20\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "#对数据合并，方便调用train_test_split函数\n",
    "Data = np.c_[X_train, y_train]\n",
    "N = 100\n",
    "#记录最小Eval对应的gamma的索引的次数\n",
    "Cnt = np.zeros(5)\n",
    "Gamma = range(5)\n",
    "\n",
    "for _ in range(N):\n",
    "    #划分数据\n",
    "    train_set, val_set = train_test_split(Data, test_size=0.2)\n",
    "    #取特征\n",
    "    X_train = train_set[:, :2]\n",
    "    #取标签\n",
    "    y_train = train_set[:, 2]\n",
    "    X_val = val_set[:, :2]\n",
    "    y_val = val_set[:, 2]\n",
    "    Eval = []\n",
    "\n",
    "    for i in Gamma:\n",
    "        gamma = 10 ** i\n",
    "        clf = svm.SVC(kernel='rbf', gamma=gamma, C=0.1)\n",
    "        clf.fit(X_train, y_train)\n",
    "        e = np.mean(clf.predict(X_val) != y_val)\n",
    "        Eval.append(e)\n",
    "    #找到最小Eval对应的索引\n",
    "    index = np.argmin(Eval)\n",
    "    #对应索引次数加1\n",
    "    Cnt[index] += 1\n",
    "    \n",
    "plt.bar(Gamma, Cnt)\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.1"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
